Case Studies Overview

Core Messaging / Positioning

Hero: "Real businesses. Real AI visibility. Real results."
Positioning: "See how local businesses across every industry have gone from invisible on AI search to the top recommendation in their area."
Success vignettes: "number one ChatGPT recommendation," "emergency plumber Tampa. we are the answer they get," mention across "ChatGPT and Perplexity."
Broad scope: "We work with every local business category — If customers search for your type of business on AI, we make sure they find you."
CTA: "Run a free AI visibility audit. See where you stand across all 5 AI engines. / Takes 4 minutes."
Meta-disclosure: "Every number below is averaged across local businesses using Bizl in their first 90 days." (Methods caveat attached to aggregated numbers.)

Claims businesses go from "invisible on AI search" to "the top recommendation in their area."
Vignettes: "#1 ChatGPT recommendation"; "we are the answer they get" for "emergency plumber Tampa" on "ChatGPT and Perplexity."
Averaging caveat: "Every number below is averaged across local businesses using Bizl in their first 90 days" — a hedge on representativeness (aggregated averages, not individual proof).
No specific percentages/volumes captured on the overview itself; numbers live in individual case-study pages.
Unsupported aggregate claims (Tier-3) moderated only by the 90-day averaging caveat.

Section: "Ready to be our next case study? Run a free AI visibility audit today. See exactly where you stand and what our team would fix first."
Funnel: free audit → done-for-you service → (member becomes next case study).

Social-proof hub: aggregate + per-vertical case studies positioned as reachable outcomes.
Horizontal claim coverage ("every local business category") to maximize search/ICP reach.
Reuses the free-audit wedge (score across all 5 AI engines, "Takes 4 minutes") as the universal CTA.
"Ready to be our next case study?" converts reader empathy into participation.
Methods caveat (first-90-day averaging) adds a veneer of rigor.

Evidence quality: Outcome claims are presented as reachable scenarios but are UNSUPPORTED aggregate anecdotes (Tier-3); the "averaged across first 90 days" caveat is a hedge, not a methodology. No underlying data, control, or verification link. DOP can differentiate with verified, individually attributable results and transparent methodology.
Silent Customer Loss framing: The core emotional sell — businesses "invisible" to the AI path that customers now use (discovery failure / customer-path leakage) — is the DOP wedge; DOP should prove the loss measured before/after.
Human supervision vs black-box: Case-study success attributed wholly to "Busy team, 90 days" narrative throughout; DOP's human-supervised method offers the same promise with visible process.
PoC-style entry: free AI visibility audit (4 min, all 5 engines) → done-for-you; matches DOP Cold Audit → PoC → Retainer.
Conversion patterns: distilled success-vignette headlines, industry-wide coverage, free-audit CTAs, aspiration-to-participation call.